IOD Dispatch: Social analytics, sports and the new CMO
Delaney Turner 270003RQ8K Delaney.Turner@ca.ibm.com | | Tags:  information-insights ibmsoftware
0 Comments | 6,079 Visits
I spent an hour yesterday at one of two Influencer Roundtables. The topic was "A closer look at the CMO: Social and Predictive Analytics, How Sports is Becoming a Metaphor for Business." On-stage to discuss the ways professional sports are becoming a "living laboratory" and the lessons they could teach CMOs were:
Here's what they said:
Leslie Ament: Social media analytics is the "flavor du jour." Are we getting a tangible return on our investment?
Deepak Advani: Marketing is evolving from an art to a science. The proliferation of channels is making it increasingly complex. We're not where we need to be but we're making tremendous progress. For example: we can now do better targeting. We can run social media data through predictive models to understand which kinds of messages will improve the sentiment toward products. Of course, CEOs will say “positive sentiment doesn't pay the bills.” That’s true, but we’re also starting to model the correlations between sentiment and purchasing behavior.
Rod Smith: We’re part of the way there. Putting analytics in the hands of the business professionals will be the next trick. When Tiger Woods makes a great shot, fan reaction will spike on Twitter and CBS will get a massive influx of viewers for the replays for half an hour. That dynamic can impact advertising. Opportunistic marketers will know how to take advantage of those opportunities.
Leslie Ament: Do organizations understand the difference between simple social media monitoring and using social analytics for business purposes?
Mark Willie: They’re getting there. The Miami Dolphins, for example, look at their media strategy across Paid, Earned and Owned media channels. That used to be all Paid. Now they’re looking at new projects that can take fan content on Facebook and Twitter and present it on the Jumbotron during games. When Chipper Jones tweets about a problem with his bathroom at a Holiday Inn, there’s someone at his door 10 minutes later. But there’s no call to the front desk.
Leslie Ament: What are the biggest challenges to implementing social analytics in sports organizations? How do you overcome them? What results have you seen?
Andrew Shelton: We’re also in the early stages. We started by collecting player data from the past few seasons and doing some basic reporting, but we didn’t take a lot of action. In sports, injuries drive performance outcomes, so we want to make more confident predictions. We’re starting to look at modeling all of our player injury data from the past few seasons – that includes training, treatment and recovery data, even collision data from sensors the players wear. From there, we're building a model to predict if they’ll be injured again.
Deepak Advani: This is the same approach that oil companies and power plants are applying to their maintenance schedules. Whether it’s player injuries or mechanical breakdowns, it’s more effective to predict and prevent failures before they happen.
Leslie Ament: So where do you start? Which variables matter?
Rod Smith: It’s easy to look at the structured information and start there, but you really need a discovery model. Sometimes structured data doesn’t reveal anything useful. So you need to pull in other data and combine it to see if the new combination has value. Also, factors are going to change over time. Predictive analytics can help you manage uncertainty over time, but it's also an iterative process. You need to look at different indicators that you think will be useful at different times.
Deepak Advani: Sometimes you don’t know which variables will impact outcomes. But if the data is there, you should try it. A perfect example of this is the Memphis Police Department. They looked to see if there was a correlation between crime rates and phases of the moon, and the changes they made because of this insight helped reduce violent crime by 28 percent.
Andrew Shelton: Our focus is to prevent injuries and protect our players’ physical welfare. So we look at every kind of variable – that adds up to 1,500 data points per player per day. It comes from GPS data collected during training, recovery from various therapies, game data and a lot more.
Leslie Ament: What steps do you take to help clients choose variables and get started?
Mark Wyllie: Every assessment begins with the same question: What are you trying to achieve? The Miami Dolphins were looking to optimize the fan experience. So we walked around the stadium for three games, one of which was a WrestleMania. We didn’t have any predefined ideas when we went in. We toured back of house operations, we talked to ushers, we simply paid attention to what was going on and took a lot of notes. Then we came up with recommendations for new signage and improving ingress/egress. The fan response was positive because they got into the stadium more quickly and team owners were happy because it meant fans bought concessions sooner, which meant they’d have more time to go back and buy more.
The challenge in sports is to keep fans coming back to the stadium. Teams need to preserve the value of their offering and offer fans experiences that they can’t get at home. In Miami, the Dolphins just rolled out a discount and loyalty card for season ticket holders. This gives them things like access to the field before the games, opportunities to meet the players, and a “Rookie Zone” that puts new fans closer to the field. All of these new new programs were driven by survey data.
Leslie Ament: Using social analytics and big data together can be very powerful. Can you cite some examples?
Deepak Advani: Remember, unstructured data isn’t just from social media. Consider call center records. Service providers have massive volumes of service records that have never been analyzed. But I know of one provider that cut customer churn from 90 percent to two percent. They did this by putting their unstructured customer data and churn data into a predictive model that connected the two data sets through customer ID numbers.
Rod Smith: Real-time data lets you “freshen up” your customer insights on a regular basis. You can monitor the performance of your messaging and stories. What are the latest things on your customers’ minds? Those will change over time. The cost of doing this has dropped dramatically.
Leslie Ament: Where are social analytics and predictive technologies going? What should best practices be five years from now?
Rod Smith: Privacy is going to be an increasingly large concern. Companies can tap into what people are saying about their products, but the rules on acting on those insights are still unclear. This is a grey area; businesses don’t want to cross that line.
Deepak Advani: Consumers will exert increasingly more control over how they engage with companies. They’re going to engage with companies on their own terms, so companies will need to pay more attention to advocates and near-advocates, as well as to detractors and near-detractors. The marketing function will change – we used to spend our time getting people to buy products or handing off leads to sales. Now, though, customers say when they’re ready to buy. The new role for marketing will be to ensure customers get the experience they expected. Customer delight can fuel a cycle of advocacy. It’s a shift from customer acquisition to customer attraction.
Leslie Ament: How do organizations tackle the cultural challenges in making this big a change?
Deepak Advani: The value of predictive analytics resonates more with the business managers, but they can also be skeptical. Will this new tool take my job? Also, they’re not terribly interested in learning about linear regressions. You need to speak in their language.
Rod Smith: You need to find a believer and do a proof of concept. You need to present it as “informed intuition.” IT also needs to rethink its role. There’s a rebalancing of the relationship between business and IT going on. There are also new delivery methodologies to consider. Take cloud, for example. Sports teams don’t want to spend on IT infrastructure, they want to spend on things that help the team win and keep the fans coming back. Cloud capabilities take control out of IT’s hands.